Overview

Brought to you by YData

Dataset statistics

Number of variables20
Number of observations2666
Missing cells3
Missing cells (%)< 0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory398.5 KiB
Average record size in memory153.0 B

Variable types

Text1
Numeric15
Categorical1
Boolean3

Alerts

Number vmail messages is highly overall correlated with Voice mail planHigh correlation
Total day charge is highly overall correlated with Total day minutesHigh correlation
Total day minutes is highly overall correlated with Total day chargeHigh correlation
Total eve charge is highly overall correlated with Total eve minutesHigh correlation
Total eve minutes is highly overall correlated with Total eve chargeHigh correlation
Total intl charge is highly overall correlated with Total intl minutesHigh correlation
Total intl minutes is highly overall correlated with Total intl chargeHigh correlation
Total night charge is highly overall correlated with Total night minutesHigh correlation
Total night minutes is highly overall correlated with Total night chargeHigh correlation
Voice mail plan is highly overall correlated with Number vmail messagesHigh correlation
International plan is highly imbalanced (52.7%) Imbalance
Number vmail messages has 1933 (72.5%) zeros Zeros
Customer service calls has 555 (20.8%) zeros Zeros

Reproduction

Analysis started2024-12-05 18:11:59.293240
Analysis finished2024-12-05 18:13:28.997603
Duration1 minute and 29.7 seconds
Software versionydata-profiling vv4.12.0
Download configurationconfig.json

Variables

State
Text

Distinct51
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size21.0 KiB
2024-12-05T18:13:29.321515image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters5332
Distinct characters24
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowKS
2nd rowOH
3rd rowNJ
4th rowOH
5th rowOK
ValueCountFrequency (%)
wv 88
 
3.3%
mn 70
 
2.6%
ny 68
 
2.6%
va 67
 
2.5%
al 66
 
2.5%
oh 66
 
2.5%
wy 66
 
2.5%
or 62
 
2.3%
nv 61
 
2.3%
wi 61
 
2.3%
Other values (41) 1991
74.7%
2024-12-05T18:13:30.470802image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 576
 
10.8%
A 550
 
10.3%
M 485
 
9.1%
I 404
 
7.6%
T 325
 
6.1%
D 305
 
5.7%
C 292
 
5.5%
O 290
 
5.4%
V 273
 
5.1%
W 263
 
4.9%
Other values (14) 1569
29.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 5332
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
N 576
 
10.8%
A 550
 
10.3%
M 485
 
9.1%
I 404
 
7.6%
T 325
 
6.1%
D 305
 
5.7%
C 292
 
5.5%
O 290
 
5.4%
V 273
 
5.1%
W 263
 
4.9%
Other values (14) 1569
29.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 5332
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
N 576
 
10.8%
A 550
 
10.3%
M 485
 
9.1%
I 404
 
7.6%
T 325
 
6.1%
D 305
 
5.7%
C 292
 
5.5%
O 290
 
5.4%
V 273
 
5.1%
W 263
 
4.9%
Other values (14) 1569
29.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 5332
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
N 576
 
10.8%
A 550
 
10.3%
M 485
 
9.1%
I 404
 
7.6%
T 325
 
6.1%
D 305
 
5.7%
C 292
 
5.5%
O 290
 
5.4%
V 273
 
5.1%
W 263
 
4.9%
Other values (14) 1569
29.4%

Account length
Real number (ℝ)

Distinct205
Distinct (%)7.7%
Missing2
Missing (%)0.1%
Infinite0
Infinite (%)0.0%
Mean100.63664
Minimum1
Maximum243
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size21.0 KiB
2024-12-05T18:13:31.064414image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile36
Q173
median100
Q3127
95-th percentile166
Maximum243
Range242
Interquartile range (IQR)54

Descriptive statistics

Standard deviation39.574152
Coefficient of variation (CV)0.39323802
Kurtosis-0.13932525
Mean100.63664
Median Absolute Deviation (MAD)27
Skewness0.077932629
Sum268096
Variance1566.1135
MonotonicityNot monotonic
2024-12-05T18:13:31.577967image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
93 35
 
1.3%
87 33
 
1.2%
105 33
 
1.2%
99 32
 
1.2%
101 32
 
1.2%
100 31
 
1.2%
86 29
 
1.1%
98 29
 
1.1%
116 29
 
1.1%
90 29
 
1.1%
Other values (195) 2352
88.2%
ValueCountFrequency (%)
1 6
0.2%
2 1
 
< 0.1%
3 4
0.2%
4 1
 
< 0.1%
5 1
 
< 0.1%
6 1
 
< 0.1%
7 1
 
< 0.1%
8 1
 
< 0.1%
9 3
0.1%
10 2
 
0.1%
ValueCountFrequency (%)
243 1
< 0.1%
225 2
0.1%
224 2
0.1%
221 1
< 0.1%
217 1
< 0.1%
212 2
0.1%
210 2
0.1%
209 1
< 0.1%
205 2
0.1%
204 1
< 0.1%

Area code
Categorical

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size21.0 KiB
415
1318 
510
679 
408
669 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters7998
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row415
2nd row415
3rd row415
4th row408
5th row415

Common Values

ValueCountFrequency (%)
415 1318
49.4%
510 679
25.5%
408 669
25.1%

Length

2024-12-05T18:13:32.008779image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-12-05T18:13:32.382294image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
ValueCountFrequency (%)
415 1318
49.4%
510 679
25.5%
408 669
25.1%

Most occurring characters

ValueCountFrequency (%)
1 1997
25.0%
5 1997
25.0%
4 1987
24.8%
0 1348
16.9%
8 669
 
8.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 7998
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1 1997
25.0%
5 1997
25.0%
4 1987
24.8%
0 1348
16.9%
8 669
 
8.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 7998
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1 1997
25.0%
5 1997
25.0%
4 1987
24.8%
0 1348
16.9%
8 669
 
8.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 7998
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1 1997
25.0%
5 1997
25.0%
4 1987
24.8%
0 1348
16.9%
8 669
 
8.4%

International plan
Boolean

Imbalance 

Distinct2
Distinct (%)0.1%
Missing1
Missing (%)< 0.1%
Memory size5.3 KiB
False
2395 
True
270 
(Missing)
 
1
ValueCountFrequency (%)
False 2395
89.8%
True 270
 
10.1%
(Missing) 1
 
< 0.1%
2024-12-05T18:13:32.599480image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Voice mail plan
Boolean

High correlation 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size2.7 KiB
False
1933 
True
733 
ValueCountFrequency (%)
False 1933
72.5%
True 733
 
27.5%
2024-12-05T18:13:32.814362image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Number vmail messages
Real number (ℝ)

High correlation  Zeros 

Distinct42
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.0217554
Minimum0
Maximum50
Zeros1933
Zeros (%)72.5%
Negative0
Negative (%)0.0%
Memory size21.0 KiB
2024-12-05T18:13:33.070026image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q319
95-th percentile36
Maximum50
Range50
Interquartile range (IQR)19

Descriptive statistics

Standard deviation13.612277
Coefficient of variation (CV)1.69692
Kurtosis-0.040157889
Mean8.0217554
Median Absolute Deviation (MAD)0
Skewness1.2717736
Sum21386
Variance185.29409
MonotonicityNot monotonic
2024-12-05T18:13:33.380993image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram with fixed size bins (bins=42)
ValueCountFrequency (%)
0 1933
72.5%
31 50
 
1.9%
28 42
 
1.6%
29 39
 
1.5%
24 37
 
1.4%
33 37
 
1.4%
30 35
 
1.3%
27 34
 
1.3%
25 33
 
1.2%
32 33
 
1.2%
Other values (32) 393
 
14.7%
ValueCountFrequency (%)
0 1933
72.5%
4 1
 
< 0.1%
8 2
 
0.1%
9 2
 
0.1%
10 1
 
< 0.1%
12 6
 
0.2%
13 3
 
0.1%
14 5
 
0.2%
15 8
 
0.3%
16 11
 
0.4%
ValueCountFrequency (%)
50 2
 
0.1%
47 3
 
0.1%
46 3
 
0.1%
45 4
 
0.2%
44 7
 
0.3%
43 9
0.3%
42 13
0.5%
41 7
 
0.3%
40 13
0.5%
39 22
0.8%

Total day minutes
Real number (ℝ)

High correlation 

Distinct1489
Distinct (%)55.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean179.48162
Minimum0
Maximum350.8
Zeros2
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size21.0 KiB
2024-12-05T18:13:33.699158image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile90.425
Q1143.4
median179.95
Q3215.9
95-th percentile269.775
Maximum350.8
Range350.8
Interquartile range (IQR)72.5

Descriptive statistics

Standard deviation54.21035
Coefficient of variation (CV)0.30203845
Kurtosis0.01936428
Mean179.48162
Median Absolute Deviation (MAD)36.25
Skewness-0.053105598
Sum478498
Variance2938.7621
MonotonicityNot monotonic
2024-12-05T18:13:34.076672image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
162.3 7
 
0.3%
183.4 7
 
0.3%
216 6
 
0.2%
175.4 6
 
0.2%
159.5 6
 
0.2%
185 6
 
0.2%
194.8 6
 
0.2%
215.6 5
 
0.2%
206.2 5
 
0.2%
124.3 5
 
0.2%
Other values (1479) 2607
97.8%
ValueCountFrequency (%)
0 2
0.1%
2.6 1
< 0.1%
7.8 1
< 0.1%
7.9 1
< 0.1%
12.5 1
< 0.1%
17.6 1
< 0.1%
18.9 1
< 0.1%
19.5 1
< 0.1%
27 1
< 0.1%
29.9 1
< 0.1%
ValueCountFrequency (%)
350.8 1
< 0.1%
346.8 1
< 0.1%
345.3 1
< 0.1%
337.4 1
< 0.1%
335.5 1
< 0.1%
329.8 1
< 0.1%
328.1 1
< 0.1%
326.3 1
< 0.1%
322.4 1
< 0.1%
322.3 1
< 0.1%

Total day calls
Real number (ℝ)

Distinct115
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean100.3102
Minimum0
Maximum160
Zeros2
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size21.0 KiB
2024-12-05T18:13:34.419956image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile67
Q187
median101
Q3114
95-th percentile133
Maximum160
Range160
Interquartile range (IQR)27

Descriptive statistics

Standard deviation19.988162
Coefficient of variation (CV)0.1992635
Kurtosis0.28954915
Mean100.3102
Median Absolute Deviation (MAD)13
Skewness-0.12826685
Sum267427
Variance399.52663
MonotonicityNot monotonic
2024-12-05T18:13:34.787483image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
105 62
 
2.3%
106 59
 
2.2%
108 59
 
2.2%
112 58
 
2.2%
102 57
 
2.1%
107 57
 
2.1%
100 56
 
2.1%
95 55
 
2.1%
104 55
 
2.1%
88 54
 
2.0%
Other values (105) 2094
78.5%
ValueCountFrequency (%)
0 2
0.1%
36 1
 
< 0.1%
40 1
 
< 0.1%
42 2
0.1%
44 3
0.1%
45 3
0.1%
47 2
0.1%
48 2
0.1%
49 2
0.1%
51 2
0.1%
ValueCountFrequency (%)
160 1
 
< 0.1%
158 3
0.1%
157 1
 
< 0.1%
156 1
 
< 0.1%
152 1
 
< 0.1%
151 5
0.2%
150 6
0.2%
149 1
 
< 0.1%
148 3
0.1%
147 5
0.2%

Total day charge
Real number (ℝ)

High correlation 

Distinct1489
Distinct (%)55.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean30.512404
Minimum0
Maximum59.64
Zeros2
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size21.0 KiB
2024-12-05T18:13:35.133190image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile15.375
Q124.38
median30.59
Q336.7
95-th percentile45.865
Maximum59.64
Range59.64
Interquartile range (IQR)12.32

Descriptive statistics

Standard deviation9.2157329
Coefficient of variation (CV)0.30203234
Kurtosis0.019501868
Mean30.512404
Median Absolute Deviation (MAD)6.16
Skewness-0.053086904
Sum81346.07
Variance84.929733
MonotonicityNot monotonic
2024-12-05T18:13:35.481027image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
27.59 7
 
0.3%
31.18 7
 
0.3%
36.72 6
 
0.2%
29.82 6
 
0.2%
27.12 6
 
0.2%
31.45 6
 
0.2%
33.12 6
 
0.2%
36.65 5
 
0.2%
35.05 5
 
0.2%
21.13 5
 
0.2%
Other values (1479) 2607
97.8%
ValueCountFrequency (%)
0 2
0.1%
0.44 1
< 0.1%
1.33 1
< 0.1%
1.34 1
< 0.1%
2.13 1
< 0.1%
2.99 1
< 0.1%
3.21 1
< 0.1%
3.32 1
< 0.1%
4.59 1
< 0.1%
5.08 1
< 0.1%
ValueCountFrequency (%)
59.64 1
< 0.1%
58.96 1
< 0.1%
58.7 1
< 0.1%
57.36 1
< 0.1%
57.04 1
< 0.1%
56.07 1
< 0.1%
55.78 1
< 0.1%
55.47 1
< 0.1%
54.81 1
< 0.1%
54.79 1
< 0.1%

Total eve minutes
Real number (ℝ)

High correlation 

Distinct1442
Distinct (%)54.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean200.38616
Minimum0
Maximum363.7
Zeros1
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size21.0 KiB
2024-12-05T18:13:35.821408image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile118.725
Q1165.3
median200.9
Q3235.1
95-th percentile285.025
Maximum363.7
Range363.7
Interquartile range (IQR)69.8

Descriptive statistics

Standard deviation50.951515
Coefficient of variation (CV)0.25426664
Kurtosis-0.025493132
Mean200.38616
Median Absolute Deviation (MAD)35
Skewness-0.012665243
Sum534229.5
Variance2596.0569
MonotonicityNot monotonic
2024-12-05T18:13:36.179217image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
169.9 8
 
0.3%
220.6 7
 
0.3%
167.2 7
 
0.3%
161.7 7
 
0.3%
224.9 6
 
0.2%
175.9 6
 
0.2%
201 6
 
0.2%
195.5 6
 
0.2%
205.1 6
 
0.2%
209.4 6
 
0.2%
Other values (1432) 2601
97.6%
ValueCountFrequency (%)
0 1
< 0.1%
31.2 1
< 0.1%
42.2 1
< 0.1%
42.5 1
< 0.1%
43.9 1
< 0.1%
49.2 1
< 0.1%
52.9 1
< 0.1%
56 1
< 0.1%
58.6 1
< 0.1%
58.9 1
< 0.1%
ValueCountFrequency (%)
363.7 1
< 0.1%
354.2 1
< 0.1%
350.9 1
< 0.1%
348.5 1
< 0.1%
347.3 1
< 0.1%
341.3 1
< 0.1%
339.9 1
< 0.1%
337.1 1
< 0.1%
335.7 1
< 0.1%
335 1
< 0.1%

Total eve calls
Real number (ℝ)

Distinct120
Distinct (%)4.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean100.02363
Minimum0
Maximum170
Zeros1
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size21.0 KiB
2024-12-05T18:13:36.515057image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile67
Q187
median100
Q3114
95-th percentile133
Maximum170
Range170
Interquartile range (IQR)27

Descriptive statistics

Standard deviation20.161445
Coefficient of variation (CV)0.20156682
Kurtosis0.18939606
Mean100.02363
Median Absolute Deviation (MAD)13.5
Skewness-0.065209284
Sum266663
Variance406.48387
MonotonicityNot monotonic
2024-12-05T18:13:36.853704image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
105 64
 
2.4%
94 62
 
2.3%
109 58
 
2.2%
102 56
 
2.1%
108 55
 
2.1%
97 54
 
2.0%
87 54
 
2.0%
115 53
 
2.0%
111 52
 
2.0%
98 52
 
2.0%
Other values (110) 2106
79.0%
ValueCountFrequency (%)
0 1
 
< 0.1%
12 1
 
< 0.1%
36 1
 
< 0.1%
42 1
 
< 0.1%
43 1
 
< 0.1%
44 1
 
< 0.1%
45 1
 
< 0.1%
46 2
 
0.1%
48 6
0.2%
49 1
 
< 0.1%
ValueCountFrequency (%)
170 1
 
< 0.1%
159 1
 
< 0.1%
157 1
 
< 0.1%
156 1
 
< 0.1%
155 2
 
0.1%
154 2
 
0.1%
153 1
 
< 0.1%
152 6
0.2%
151 1
 
< 0.1%
150 3
0.1%

Total eve charge
Real number (ℝ)

High correlation 

Distinct1301
Distinct (%)48.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean17.033072
Minimum0
Maximum30.91
Zeros1
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size21.0 KiB
2024-12-05T18:13:37.188075image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile10.0925
Q114.05
median17.08
Q319.98
95-th percentile24.225
Maximum30.91
Range30.91
Interquartile range (IQR)5.93

Descriptive statistics

Standard deviation4.3308642
Coefficient of variation (CV)0.25426207
Kurtosis-0.025570134
Mean17.033072
Median Absolute Deviation (MAD)2.98
Skewness-0.012629035
Sum45410.17
Variance18.756385
MonotonicityNot monotonic
2024-12-05T18:13:37.551618image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
16.12 9
 
0.3%
14.25 9
 
0.3%
18.62 8
 
0.3%
17.99 8
 
0.3%
18.96 8
 
0.3%
17.43 8
 
0.3%
14.44 8
 
0.3%
16.63 7
 
0.3%
15.9 7
 
0.3%
18.79 7
 
0.3%
Other values (1291) 2587
97.0%
ValueCountFrequency (%)
0 1
< 0.1%
2.65 1
< 0.1%
3.59 1
< 0.1%
3.61 1
< 0.1%
3.73 1
< 0.1%
4.18 1
< 0.1%
4.5 1
< 0.1%
4.76 1
< 0.1%
4.98 1
< 0.1%
5.01 1
< 0.1%
ValueCountFrequency (%)
30.91 1
< 0.1%
30.11 1
< 0.1%
29.83 1
< 0.1%
29.62 1
< 0.1%
29.52 1
< 0.1%
29.01 1
< 0.1%
28.89 1
< 0.1%
28.65 1
< 0.1%
28.53 1
< 0.1%
28.48 1
< 0.1%

Total night minutes
Real number (ℝ)

High correlation 

Distinct1444
Distinct (%)54.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean201.16894
Minimum43.7
Maximum395
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size21.0 KiB
2024-12-05T18:13:37.877313image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Quantile statistics

Minimum43.7
5-th percentile117.925
Q1166.925
median201.15
Q3236.475
95-th percentile283.675
Maximum395
Range351.3
Interquartile range (IQR)69.55

Descriptive statistics

Standard deviation50.780323
Coefficient of variation (CV)0.25242626
Kurtosis0.050382274
Mean201.16894
Median Absolute Deviation (MAD)34.8
Skewness0.0233625
Sum536316.4
Variance2578.6412
MonotonicityNot monotonic
2024-12-05T18:13:38.233551image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
214.7 7
 
0.3%
181.2 6
 
0.2%
172.7 6
 
0.2%
210 6
 
0.2%
214 6
 
0.2%
182.1 6
 
0.2%
192.7 6
 
0.2%
194.3 6
 
0.2%
193.6 6
 
0.2%
197.4 6
 
0.2%
Other values (1434) 2605
97.7%
ValueCountFrequency (%)
43.7 1
< 0.1%
45 1
< 0.1%
47.4 1
< 0.1%
50.1 2
0.1%
53.3 1
< 0.1%
54 1
< 0.1%
54.5 1
< 0.1%
56.6 1
< 0.1%
57.5 1
< 0.1%
63.3 1
< 0.1%
ValueCountFrequency (%)
395 1
< 0.1%
381.9 1
< 0.1%
377.5 1
< 0.1%
364.9 1
< 0.1%
364.3 1
< 0.1%
354.9 1
< 0.1%
352.5 1
< 0.1%
352.2 1
< 0.1%
350.2 1
< 0.1%
349.2 1
< 0.1%

Total night calls
Real number (ℝ)

Distinct118
Distinct (%)4.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean100.10615
Minimum33
Maximum166
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size21.0 KiB
2024-12-05T18:13:38.580615image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Quantile statistics

Minimum33
5-th percentile68
Q187
median100
Q3113
95-th percentile131
Maximum166
Range133
Interquartile range (IQR)26

Descriptive statistics

Standard deviation19.418459
Coefficient of variation (CV)0.19397867
Kurtosis-0.048008683
Mean100.10615
Median Absolute Deviation (MAD)13
Skewness0.010410401
Sum266883
Variance377.07653
MonotonicityNot monotonic
2024-12-05T18:13:38.963569image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
105 70
 
2.6%
104 67
 
2.5%
91 60
 
2.3%
106 58
 
2.2%
102 58
 
2.2%
100 57
 
2.1%
96 54
 
2.0%
108 53
 
2.0%
95 53
 
2.0%
98 53
 
2.0%
Other values (108) 2083
78.1%
ValueCountFrequency (%)
33 1
< 0.1%
36 1
< 0.1%
38 1
< 0.1%
42 1
< 0.1%
44 1
< 0.1%
46 1
< 0.1%
48 1
< 0.1%
49 2
0.1%
50 2
0.1%
51 2
0.1%
ValueCountFrequency (%)
166 1
 
< 0.1%
164 1
 
< 0.1%
158 1
 
< 0.1%
157 2
0.1%
156 2
0.1%
155 1
 
< 0.1%
154 2
0.1%
153 3
0.1%
152 3
0.1%
151 2
0.1%

Total night charge
Real number (ℝ)

High correlation 

Distinct885
Distinct (%)33.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9.0526894
Minimum1.97
Maximum17.77
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size21.0 KiB
2024-12-05T18:13:39.293242image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Quantile statistics

Minimum1.97
5-th percentile5.31
Q17.5125
median9.05
Q310.64
95-th percentile12.7675
Maximum17.77
Range15.8
Interquartile range (IQR)3.1275

Descriptive statistics

Standard deviation2.2851195
Coefficient of variation (CV)0.25242438
Kurtosis0.050081231
Mean9.0526894
Median Absolute Deviation (MAD)1.565
Skewness0.023318474
Sum24134.47
Variance5.2217712
MonotonicityNot monotonic
2024-12-05T18:13:39.648498image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
9.66 13
 
0.5%
8.88 11
 
0.4%
7.15 10
 
0.4%
9.63 10
 
0.4%
9.14 10
 
0.4%
9.32 9
 
0.3%
9.45 9
 
0.3%
8.15 9
 
0.3%
10.49 9
 
0.3%
6.48 9
 
0.3%
Other values (875) 2567
96.3%
ValueCountFrequency (%)
1.97 1
< 0.1%
2.03 1
< 0.1%
2.13 1
< 0.1%
2.25 2
0.1%
2.4 1
< 0.1%
2.43 1
< 0.1%
2.45 1
< 0.1%
2.55 1
< 0.1%
2.59 1
< 0.1%
2.85 1
< 0.1%
ValueCountFrequency (%)
17.77 1
< 0.1%
17.19 1
< 0.1%
16.99 1
< 0.1%
16.42 1
< 0.1%
16.39 1
< 0.1%
15.97 1
< 0.1%
15.86 1
< 0.1%
15.85 1
< 0.1%
15.76 1
< 0.1%
15.71 1
< 0.1%

Total intl minutes
Real number (ℝ)

High correlation 

Distinct158
Distinct (%)5.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10.237022
Minimum0
Maximum20
Zeros15
Zeros (%)0.6%
Negative0
Negative (%)0.0%
Memory size21.0 KiB
2024-12-05T18:13:40.019258image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile5.8
Q18.5
median10.2
Q312.1
95-th percentile14.7
Maximum20
Range20
Interquartile range (IQR)3.6

Descriptive statistics

Standard deviation2.7883486
Coefficient of variation (CV)0.27237889
Kurtosis0.61655483
Mean10.237022
Median Absolute Deviation (MAD)1.8
Skewness-0.22443425
Sum27291.9
Variance7.7748878
MonotonicityNot monotonic
2024-12-05T18:13:40.378128image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10 54
 
2.0%
10.2 47
 
1.8%
9.8 45
 
1.7%
11.5 43
 
1.6%
10.6 42
 
1.6%
9.1 42
 
1.6%
11.3 42
 
1.6%
10.9 41
 
1.5%
11.4 41
 
1.5%
9.7 41
 
1.5%
Other values (148) 2228
83.6%
ValueCountFrequency (%)
0 15
0.6%
1.1 1
 
< 0.1%
1.3 1
 
< 0.1%
2.1 1
 
< 0.1%
2.2 1
 
< 0.1%
2.4 1
 
< 0.1%
2.5 1
 
< 0.1%
2.6 1
 
< 0.1%
2.9 2
 
0.1%
3.1 1
 
< 0.1%
ValueCountFrequency (%)
20 1
 
< 0.1%
18.9 1
 
< 0.1%
18.4 1
 
< 0.1%
18.2 2
0.1%
18 2
0.1%
17.9 1
 
< 0.1%
17.8 2
0.1%
17.6 2
0.1%
17.5 3
0.1%
17.3 2
0.1%

Total intl calls
Real number (ℝ)

Distinct21
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.4673668
Minimum0
Maximum20
Zeros15
Zeros (%)0.6%
Negative0
Negative (%)0.0%
Memory size21.0 KiB
2024-12-05T18:13:40.710932image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q13
median4
Q36
95-th percentile9
Maximum20
Range20
Interquartile range (IQR)3

Descriptive statistics

Standard deviation2.4561949
Coefficient of variation (CV)0.5498082
Kurtosis3.2666188
Mean4.4673668
Median Absolute Deviation (MAD)1
Skewness1.3587685
Sum11910
Variance6.0328934
MonotonicityNot monotonic
2024-12-05T18:13:41.652464image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
3 544
20.4%
4 503
18.9%
2 388
14.6%
5 376
14.1%
6 267
10.0%
7 172
 
6.5%
1 125
 
4.7%
8 90
 
3.4%
9 83
 
3.1%
10 37
 
1.4%
Other values (11) 81
 
3.0%
ValueCountFrequency (%)
0 15
 
0.6%
1 125
 
4.7%
2 388
14.6%
3 544
20.4%
4 503
18.9%
5 376
14.1%
6 267
10.0%
7 172
 
6.5%
8 90
 
3.4%
9 83
 
3.1%
ValueCountFrequency (%)
20 1
 
< 0.1%
19 1
 
< 0.1%
18 2
 
0.1%
17 1
 
< 0.1%
16 2
 
0.1%
15 4
 
0.2%
14 5
 
0.2%
13 13
0.5%
12 12
0.5%
11 25
0.9%

Total intl charge
Real number (ℝ)

High correlation 

Distinct158
Distinct (%)5.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.7644899
Minimum0
Maximum5.4
Zeros15
Zeros (%)0.6%
Negative0
Negative (%)0.0%
Memory size21.0 KiB
2024-12-05T18:13:42.001791image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1.57
Q12.3
median2.75
Q33.27
95-th percentile3.97
Maximum5.4
Range5.4
Interquartile range (IQR)0.97

Descriptive statistics

Standard deviation0.75281205
Coefficient of variation (CV)0.272315
Kurtosis0.61753714
Mean2.7644899
Median Absolute Deviation (MAD)0.49
Skewness-0.22456853
Sum7370.13
Variance0.56672599
MonotonicityNot monotonic
2024-12-05T18:13:42.415239image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2.7 54
 
2.0%
2.75 47
 
1.8%
2.65 45
 
1.7%
3.11 43
 
1.6%
2.86 42
 
1.6%
2.46 42
 
1.6%
3.05 42
 
1.6%
2.94 41
 
1.5%
3.08 41
 
1.5%
2.62 41
 
1.5%
Other values (148) 2228
83.6%
ValueCountFrequency (%)
0 15
0.6%
0.3 1
 
< 0.1%
0.35 1
 
< 0.1%
0.57 1
 
< 0.1%
0.59 1
 
< 0.1%
0.65 1
 
< 0.1%
0.68 1
 
< 0.1%
0.7 1
 
< 0.1%
0.78 2
 
0.1%
0.84 1
 
< 0.1%
ValueCountFrequency (%)
5.4 1
 
< 0.1%
5.1 1
 
< 0.1%
4.97 1
 
< 0.1%
4.91 2
0.1%
4.86 2
0.1%
4.83 1
 
< 0.1%
4.81 2
0.1%
4.75 2
0.1%
4.73 3
0.1%
4.67 2
0.1%

Customer service calls
Real number (ℝ)

Zeros 

Distinct10
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.5626407
Minimum0
Maximum9
Zeros555
Zeros (%)20.8%
Negative0
Negative (%)0.0%
Memory size21.0 KiB
2024-12-05T18:13:42.929483image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median1
Q32
95-th percentile4
Maximum9
Range9
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.3112358
Coefficient of variation (CV)0.83911535
Kurtosis1.813987
Mean1.5626407
Median Absolute Deviation (MAD)1
Skewness1.0951763
Sum4166
Variance1.7193392
MonotonicityNot monotonic
2024-12-05T18:13:43.427749image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
1 945
35.4%
2 608
22.8%
0 555
20.8%
3 348
 
13.1%
4 133
 
5.0%
5 49
 
1.8%
6 17
 
0.6%
7 8
 
0.3%
9 2
 
0.1%
8 1
 
< 0.1%
ValueCountFrequency (%)
0 555
20.8%
1 945
35.4%
2 608
22.8%
3 348
 
13.1%
4 133
 
5.0%
5 49
 
1.8%
6 17
 
0.6%
7 8
 
0.3%
8 1
 
< 0.1%
9 2
 
0.1%
ValueCountFrequency (%)
9 2
 
0.1%
8 1
 
< 0.1%
7 8
 
0.3%
6 17
 
0.6%
5 49
 
1.8%
4 133
 
5.0%
3 348
 
13.1%
2 608
22.8%
1 945
35.4%
0 555
20.8%

Churn
Boolean

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size2.7 KiB
False
2278 
True
388 
ValueCountFrequency (%)
False 2278
85.4%
True 388
 
14.6%
2024-12-05T18:13:43.829624image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Interactions

2024-12-05T18:13:23.540221image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-12-05T18:12:01.100332image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-12-05T18:12:10.103049image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-12-05T18:12:17.353650image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-12-05T18:12:28.259407image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-12-05T18:12:38.733295image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-12-05T18:12:43.405359image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-12-05T18:12:47.690944image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-12-05T18:12:52.960810image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-12-05T18:12:56.843129image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-12-05T18:13:00.912368image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-12-05T18:13:06.249917image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-12-05T18:13:10.138459image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-12-05T18:13:14.095736image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-12-05T18:13:19.256998image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-12-05T18:13:23.791008image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-12-05T18:12:01.387684image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-12-05T18:12:10.534074image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-12-05T18:12:18.682199image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-12-05T18:12:29.118808image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-12-05T18:12:39.718332image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-12-05T18:12:43.657487image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-12-05T18:12:48.070306image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-12-05T18:12:53.205262image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-12-05T18:12:57.081887image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-12-05T18:13:01.234410image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-12-05T18:13:06.529359image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-12-05T18:13:10.392210image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-12-05T18:13:14.347232image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-12-05T18:13:19.484846image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-12-05T18:13:24.024369image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-12-05T18:12:01.636800image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-12-05T18:12:11.064813image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-12-05T18:12:19.624977image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-12-05T18:12:29.828432image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-12-05T18:12:40.043987image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-12-05T18:12:43.897556image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-12-05T18:12:48.457094image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-12-05T18:12:53.448264image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-12-05T18:12:57.344517image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-12-05T18:13:01.565588image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-12-05T18:13:06.787057image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-12-05T18:13:10.663434image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-12-05T18:13:14.700111image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-12-05T18:13:19.725486image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-12-05T18:13:24.275919image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-12-05T18:12:01.957519image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-12-05T18:12:11.519668image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-12-05T18:12:20.307030image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-12-05T18:12:30.292523image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-12-05T18:12:40.304581image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-12-05T18:12:44.153842image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-12-05T18:12:48.850825image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-12-05T18:12:53.707838image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-12-05T18:12:57.602389image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-12-05T18:13:01.919618image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-12-05T18:13:07.047474image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-12-05T18:13:10.932225image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-12-05T18:13:15.131470image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-12-05T18:13:19.977980image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-12-05T18:13:24.570015image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-12-05T18:12:02.383670image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
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2024-12-05T18:12:49.266014image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
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2024-12-05T18:12:57.869589image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
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2024-12-05T18:13:07.313530image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
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2024-12-05T18:12:36.261781image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
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2024-12-05T18:13:13.863724image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-12-05T18:13:19.008266image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-12-05T18:13:23.288054image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Correlations

2024-12-05T18:13:44.170635image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Account lengthArea codeChurnCustomer service callsInternational planNumber vmail messagesTotal day callsTotal day chargeTotal day minutesTotal eve callsTotal eve chargeTotal eve minutesTotal intl callsTotal intl chargeTotal intl minutesTotal night callsTotal night chargeTotal night minutesVoice mail plan
Account length1.0000.0380.0000.0020.0000.0020.0340.0160.0160.016-0.020-0.0200.0280.0170.017-0.018-0.010-0.0100.023
Area code0.0381.0000.0000.0290.0400.0000.0000.0390.0380.0270.0000.0000.0000.0000.0000.0000.0000.0000.000
Churn0.0000.0001.0000.3210.2750.1080.0600.3430.3440.0000.0500.0500.0930.0680.0680.0280.0710.0700.096
Customer service calls0.0020.0290.3211.0000.067-0.022-0.011-0.025-0.0250.001-0.015-0.015-0.005-0.011-0.011-0.0020.0010.0010.014
International plan0.0000.0400.2750.0671.0000.0000.0570.0660.0670.0000.0290.0300.0350.0380.0380.0170.0170.0170.000
Number vmail messages0.0020.0000.108-0.0220.0001.000-0.0150.0240.024-0.0000.0180.0180.015-0.014-0.0140.011-0.004-0.0040.998
Total day calls0.0340.0000.060-0.0110.057-0.0151.0000.0130.0130.016-0.020-0.0200.0040.0240.024-0.0170.0070.0070.000
Total day charge0.0160.0390.343-0.0250.0660.0240.0131.0001.0000.0150.0080.008-0.002-0.016-0.0160.0160.0030.0030.048
Total day minutes0.0160.0380.344-0.0250.0670.0240.0131.0001.0000.0150.0080.008-0.002-0.016-0.0160.0160.0030.0030.049
Total eve calls0.0160.0270.0000.0010.000-0.0000.0160.0150.0151.000-0.007-0.007-0.003-0.001-0.001-0.0030.0060.0060.000
Total eve charge-0.0200.0000.050-0.0150.0290.018-0.0200.0080.008-0.0071.0001.0000.016-0.002-0.0020.006-0.012-0.0120.000
Total eve minutes-0.0200.0000.050-0.0150.0300.018-0.0200.0080.008-0.0071.0001.0000.016-0.002-0.0020.006-0.012-0.0120.000
Total intl calls0.0280.0000.093-0.0050.0350.0150.004-0.002-0.002-0.0030.0160.0161.0000.0180.0180.0160.0150.0150.000
Total intl charge0.0170.0000.068-0.0110.038-0.0140.024-0.016-0.016-0.001-0.002-0.0020.0181.0001.000-0.020-0.004-0.0040.000
Total intl minutes0.0170.0000.068-0.0110.038-0.0140.024-0.016-0.016-0.001-0.002-0.0020.0181.0001.000-0.020-0.004-0.0040.000
Total night calls-0.0180.0000.028-0.0020.0170.011-0.0170.0160.016-0.0030.0060.0060.016-0.020-0.0201.0000.0090.0090.005
Total night charge-0.0100.0000.0710.0010.017-0.0040.0070.0030.0030.006-0.012-0.0120.015-0.004-0.0040.0091.0001.0000.000
Total night minutes-0.0100.0000.0700.0010.017-0.0040.0070.0030.0030.006-0.012-0.0120.015-0.004-0.0040.0091.0001.0000.000
Voice mail plan0.0230.0000.0960.0140.0000.9980.0000.0480.0490.0000.0000.0000.0000.0000.0000.0050.0000.0001.000

Missing values

2024-12-05T18:13:27.478760image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
A simple visualization of nullity by column.
2024-12-05T18:13:28.158869image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2024-12-05T18:13:28.713593image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

StateAccount lengthArea codeInternational planVoice mail planNumber vmail messagesTotal day minutesTotal day callsTotal day chargeTotal eve minutesTotal eve callsTotal eve chargeTotal night minutesTotal night callsTotal night chargeTotal intl minutesTotal intl callsTotal intl chargeCustomer service callsChurn
0KS128.0415NaNYes25265.111045.07197.49916.78244.79111.0110.032.701False
1OH107.0415NoYes26161.612327.47195.510316.62254.410311.4513.733.701False
2NJ137.0415NoNo0243.411441.38121.211010.30162.61047.3212.253.290False
3OHNaN408YesNo0299.47150.9061.9885.26196.9898.866.671.782False
4OK75.0415YesNo0166.711328.34148.312212.61186.91218.4110.132.733False
5AL118.0510YesNo0223.49837.98220.610118.75203.91189.186.361.700False
6MA121.0510NoYes24218.28837.09348.510829.62212.61189.577.572.033False
7MO147.0415YesNo0157.07926.69103.1948.76211.8969.537.161.920False
8WV141.0415YesYes37258.68443.96222.011118.87326.49714.6911.253.020False
9RINaN415NoNo0187.712731.91163.414813.89196.0948.829.152.460False
StateAccount lengthArea codeInternational planVoice mail planNumber vmail messagesTotal day minutesTotal day callsTotal day chargeTotal eve minutesTotal eve callsTotal eve chargeTotal night minutesTotal night callsTotal night chargeTotal intl minutesTotal intl callsTotal intl chargeCustomer service callsChurn
2656GA122.0510YesNo0140.010123.80196.47716.69120.11335.409.742.624True
2657MD62.0408NoNo0321.110554.59265.512222.57180.5728.1211.523.114True
2658IN117.0415NoNo0118.412620.13249.39721.19227.05610.2213.633.675True
2659OH78.0408NoNo0193.49932.88116.9889.94243.310910.959.342.512False
2660OH96.0415NoNo0106.612818.12284.88724.21178.9928.0514.974.021False
2661SC79.0415NoNo0134.79822.90189.76816.12221.41289.9611.853.192False
2662AZ192.0415NoYes36156.27726.55215.512618.32279.18312.569.962.672False
2663WV68.0415NoNo0231.15739.29153.45513.04191.31238.619.642.593False
2664RI28.0510NoNo0180.810930.74288.85824.55191.9918.6414.163.812False
2665TN74.0415NoYes25234.411339.85265.98222.60241.47710.8613.743.700False